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The location-allocation model for multi-classification-yard location problem

Author

Listed:
  • Lin, Boliang
  • Liu, Siqi
  • Lin, Ruixi
  • Wang, Jiaxi
  • Sun, Min
  • Wang, Xiaodong
  • Liu, Chang
  • Wu, Jianping
  • Xiao, Jie

Abstract

This paper proposes a bi-level programming model for the multi-classification-yard location (MCYL) problem. The upper-level is intended to find an optimal establishment or improvement strategy for candidate nodes with a budget constraint, which is involved with the selection of potential yard locations and the determination of yard size and capacity. The lower-level aims to obtain the least costly plan of railcar reclassification considering yard classification capacity and tracks, on the basis of the strategy given by the upper-level. A simulated annealing (SA) algorithm is then applied to solve the MCYL problem of a large-scale China railway network.

Suggested Citation

  • Lin, Boliang & Liu, Siqi & Lin, Ruixi & Wang, Jiaxi & Sun, Min & Wang, Xiaodong & Liu, Chang & Wu, Jianping & Xiao, Jie, 2019. "The location-allocation model for multi-classification-yard location problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 283-308.
    • Handle: RePEc:eee:transe:v:122:y:2019:i:c:p:283-308
    DOI: 10.1016/j.tre.2018.12.013
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    References listed on IDEAS

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    Cited by:

    1. Jeffrey Steven Paulson & Anil Raj Kizha & Han-Sup Han, 2019. "Integrating Biomass Conversion Technologies with Recovery Operations In-Woods: Modeling Supply Chain," Logistics, MDPI, vol. 3(3), pages 1-14, July.
    2. Fadda, Edoardo & Manerba, Daniele & Cabodi, Gianpiero & Camurati, Paolo Enrico & Tadei, Roberto, 2021. "Comparative analysis of models and performance indicators for optimal service facility location," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).

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